Gesture recognition method and gesture recognition device

ABSTRACT

A gesture recognition method and a gesture recognition device are provided. The gesture recognition method includes the steps of: obtaining a hand image including a gesture graphic; determining a reference point in the gesture graphic; determining circular arc reference lines by using the reference point as a center; determining intersection points of each of the circular arc reference lines intersecting with a boundary of the gesture graphic; determining whether at least two finger blocks of a plurality of finger blocks of the gesture graphic conform to an approaching trend according to the circular arc reference lines and the intersection points, and determining whether the at least two finger blocks in a selected range of the gesture graphic forms a continuous graphic block; and when the at least two finger blocks of the gesture graphic conform to the approaching trend and form the continuous graphic block, determining the hand image as a hand pinch image.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority benefit of Taiwan applicationserial no. 108107629, filed on Mar. 7, 2019. The entirety of theabove-mentioned patent application is hereby incorporated by referenceherein and made a part of this specification.

BACKGROUND Technical Field

The disclosure relates to a recognition technique, and moreparticularly, to a gesture recognition method and a gesture recognitiondevice.

Description of Related Art

In general, the early human-machine interaction functions of varioushead-mounted displays (HMD) for virtual reality (VR)/augmented reality(AR) could not enter the general consumer market due to the limitationsof the computing processing speed, the big and heavy device body, thelack of supporting application software, and the high price. However, inrecent years, electronic hardware technology has greatly improved, thehardware computing processing capability has been significantlyenhanced, and the development of application software has alsoincreased. Therefore, there has been a boom in application designsrelated to HMD devices in recent years. Moreover, with thepopularization of mobile devices, product development of HMD devicesmostly moves toward designs that are compact and lightweight butmeanwhile have high processing power.

To enable the HMD device to provide a simulated interactive experiencewith the virtual environment, the HMD device is generally equipped witha sensor or a lens to capture and determine the user's gesture. In thisregard, in the human-machine interaction functions of the HMD device,how to effectively determine the gesture/action of the user in anaccurate and rapid manner has always been one of the important issues inthe field. For example, in the case of pinch gesture recognition, theimage analysis method of a general HMD device involves capturing theentire image including the hand image of the user in front of the lensand then performing image recognition processing on the entire image todetermine whether the hand is in a pinch gesture and subsequentlyperform other corresponding software interaction functions. However,with the computing resources being limited by the physical size and thecosts, the HMD device may not be able to support such a large datacomputation amount or may not be able to provide the recognitionfunction in real-time. In view of the above, to realize accurate gesturerecognition effect in real-time without consuming a lot of computingresources, the disclosure will provide a solution of at least oneembodiment in the description below.

SUMMARY

In view of the above, the disclosure provides a gesture recognitionmethod and a gesture recognition device that can effectively analyze ahand image of a user to accurately recognize whether the user's gestureis a pinch gesture.

A gesture recognition method according to an embodiment of thedisclosure includes the following steps. A hand image is obtained,wherein the hand image includes a gesture graphic. A reference point inthe gesture graphic is determined. A plurality of circular arc referencelines are determined by using the reference point as a center. Aplurality of intersection points of each of the circular arc referencelines intersecting with a boundary of the gesture graphic aredetermined. It is determined whether at least two finger blocks of aplurality of finger blocks of the gesture graphic conform to anapproaching trend according to the plurality of circular arc referencelines and the plurality of intersection points, and it is determinedwhether the at least two finger blocks in a selected range of thegesture graphic form a continuous graphic block. When the at least twofinger blocks of the gesture graphic conform to the approaching trendand form the continuous graphic block, the hand image is determined tobe a hand pinch image.

A gesture recognition device according to an embodiment of thedisclosure includes an image capturing device and a processor. The imagecapturing device is configured to obtain a hand image. The hand imageincludes a gesture graphic. The processor is electrically coupled to theimage capturing device. The processor is configured to analyze thegesture graphic of the hand image to determine a reference point in thegesture graphic. The processor determines a plurality of circular arcreference lines by using the reference point as a center, and determinesa plurality of intersection points of each of the circular arc referencelines intersecting with a boundary of the gesture graphic. The processordetermines whether at least two finger blocks of a plurality of fingerblocks of the gesture graphic conform to an approaching trend accordingto the plurality of circular arc reference lines and the plurality ofintersection points, and determines whether the at least two fingerblocks in a selected range of the gesture graphic form a continuousgraphic block. When the at least two finger blocks of the gesturegraphic conform to the approaching trend and form the continuous graphicblock, the processor determines that the hand image is a hand pinchimage.

Based on the above, the gesture recognition method and the gesturerecognition device of the disclosure can analyze the hand image of theuser in real-time to first determine whether the plurality of fingerblocks of the gesture graphic in the hand image conform to theapproaching trend, and then determine whether the finger blocks form acontinuous graphic block, so as to determine whether the hand image ofthe user is a hand pinch image. Therefore, the gesture recognitionmethod and the gesture recognition device of the disclosure canaccurately recognize whether the user's gesture is a pinch gesture.

To make the aforementioned more comprehensible, several embodimentsaccompanied with drawings are described in detail as follows.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic view of a gesture recognition device according toan embodiment of the disclosure.

FIG. 2 is a flowchart of hand image analysis according to an embodimentof the disclosure.

FIG. 3 is a schematic view of analysis on a hand image according to anembodiment of the disclosure.

FIG. 4 is a schematic view of analysis on another hand image accordingto an embodiment of the disclosure.

FIG. 5 is a flowchart of a gesture recognition method according to anembodiment of the disclosure.

DESCRIPTION OF THE EMBODIMENTS

To make the content of the disclosure more comprehensible, at least oneembodiment will be provided below as an example for implementing thedisclosure accordingly. In addition, wherever possible, elements,components, and steps labeled with the same numerals in the drawings andthe embodiments represent the same or similar parts.

FIG. 1 is a schematic view of a gesture recognition device according toan embodiment of the disclosure. Referring to FIG. 1, a gesturerecognition device 100 includes a processor 110, an image capturingdevice 120, a storage 130, and a gesture recognition program 131 that isstored in the storage 130 and may be loaded and executed by theprocessor 110. The processor 110 is electrically coupled to the imagecapturing device 120. In the present embodiment, the gesture recognitiondevice 100 is, for example, applicable to various electronic devices ormultimedia devices to provide a real-time gesture recognition function.Particularly, in specific embodiments, the gesture recognition device100 of the disclosure may be combined with or applied to a head-mounteddisplay (HMD) for virtual reality (VR) or augmented reality (AR), butthe disclosure is not limited thereto. The gesture recognition device100 of the present embodiment may provide a gesture recognition functionand provide a gesture recognition result to a backend application or abackend device to perform other corresponding functions or operations.

Specifically, when a user's hand is located in front of the imagecapturing device 120, and the gesture recognition device 100 isperforming the gesture recognition function, the image capturing device120 obtains a hand image of the user, and the hand image includes agesture graphic. Next, the image capturing device 120 provides the handimage to the gesture recognition program 131 to cause the processor 110to perform image analysis. It is noted that the gesture recognitiondevice 100 of the present embodiment is configured to provide a functionof effectively determining whether a gesture of the user is a pinchgesture (e.g., an action in which the end of the user's thumb is incontact with the end of the index finger, and the rest of the fingersare folded against the palm; however, the disclosure is not limitedthereto, and the end of the thumb may be in contact with the end ofother one or more fingers). In other words, the processor 110 determineswhether the hand image is a hand pinch image. In addition, in thepresent embodiment, the hand image analyzed by the processor 110 may bea grayscale or grayscale-processed image which further undergoesbinarization processing, and the region in the gesture graphic and theregion outside the gesture graphic in the hand image have differentpixel values.

In the present embodiment, the processor 110 may be a graphicsprocessing unit (GPU), an image signal processor (ISP), a centralprocessing unit (CPU), another programmable general-purpose orspecific-purpose microprocessor, digital signal processor (DSP),programmable controller, application specific integrated circuit (ASIC),programmable logic device (PLD), another similar processor, or acombination of the above processor circuits. Moreover, the gesturerecognition device 100 of the present embodiment may further include amemory 140. The memory 140 may be configured to store image data 141obtained by the image capturing device 120 and the image data 141 thatis temporarily stored during processing of the gesture recognitionprogram.

In the present embodiment, the image capturing device 120 may be a depthcamera, an infrared camera, or an RGB camera. Taking the depth camera asan example, when the user's hand is located in front of the depthcamera, the depth camera may obtain a hand image of the user based onthe closer foreground through a determination of the distance thresholdvalue. Taking the infrared camera as an example, when the user's hand islocated in front of the infrared camera, the infrared camera may obtainthe hand image by determining the region having the highest reflectionbrightness. Taking the RGB camera as an example, when the user's hand islocated in front of the infrared camera, the RGB camera may find aregion that is most similar to a hand through a pre-designed trainingmodel or a relevant learning algorithm to obtain the hand image.

Further, in an embodiment, if the image capturing device 120 is a depthcamera or an RGB camera, the processor 110 first performs image datasimplification on the hand image provided by the image capturing device120. In other words, the processor 110 may first perform binarizationprocessing on the hand image to facilitate subsequent image analysis.However, in another embodiment, if the image capturing device 120 is aninfrared camera, since the image data provided by the infrared camera isalready a grayscale image, the processor 110 may first perform fastbinarization processing on the grayscale hand image, and then performsubsequent image analysis. In even another embodiment, if the hand imageprovided by the infrared camera is already a binary black-and-whiteimage, the processor 110 may directly analyze the hand image provided bythe infrared camera, and the processor 110 is not required toadditionally perform binarization processing.

FIG. 2 is a flowchart of hand image analysis according to an embodimentof the disclosure. Referring to FIG. 1 and FIG. 2, after being loaded,the gesture recognition program 131 of the gesture recognition device100 may perform steps S210 to S290 of FIG. 2 to realize the gesturerecognition function. In step S210, the gesture recognition device 100obtains a hand image through the image capturing device 120 and providesthe hand image to the processor 110 to cause the processor 110 toanalyze the hand image. It is noted that the hand image analyzed by theprocessor 110 is a binarized image. However, whether processor 110performs binarization processing on the hand image depends on the typeof the image capturing device 120. In step S220, the processor 110analyzes the hand image to determine a reference point in a gesturegraphic of the hand image. In step S230, the processor 110 determines aplurality of circular arc reference lines by using the reference pointas a center. In step S240, the processor 110 determines a number offingers according to the plurality of circular arc reference lines. Instep S250, the processor 110 determines a finger trend of the gesturegraphic according to the plurality of circular arc reference lines. Instep S260, the processor 110 determines whether a trend in which atleast two fingers are approaching each other is present in the fingertrend. If negative, the processor 110 performs step S210 again to obtaina next hand image. If affirmative, the processor 110 performs step S270to recognize a number of finger blocks of the gesture graphic.

In step S270, the processor 110 recognizes a number of finger blocks ofthe gesture graphic according to the plurality of circular arc referencelines. In step S280, the processor 110 determines whether the number ofthe finger blocks of the gesture graphic is one. If negative, theprocessor 110 performs step S210 again to obtain a next hand image. Ifaffirmative, the processor 110 performs step S290 to output a gesturerecognition result as a pinch gesture. In other words, in the presentembodiment, the gesture recognition device 100 performs recognition intwo stages. In the first stage, the processor 110 first analyzes whethera trend in which at least two fingers are approaching each other ispresent in the finger trend of the gesture graphic to indicate that theuser's gesture may be a pinch gesture. If the gesture graphic in thehand image satisfies the above condition in the first stage, theprocessor 110 performs the second stage. In the second stage, theprocessor 110 further analyzes the number of the finger blocks of thegesture graphic. If the number of the finger blocks of the gesturegraphic is one, it means that a plurality of finger blocks are connectedto each other to form a continuous graphic block, and that the user'sfinger action is a pinch action. Conversely, if the finger blocks of thegesture graphic is not a continuous graphic block, it means that theuser's finger action is not a pinch action. Accordingly, the gesturerecognition device 100 of the present embodiment can provide an accuratereal-time pinch gesture recognition result.

To allow those skilled in the art to further understand theimplementation details of the gesture recognition of the disclosure, twodifferent examples of the hand image as presented in FIG. 3 and FIG. 4will be described in detail below.

FIG. 3 is a schematic view of analysis on a hand image according to anembodiment of the disclosure. Reference is made to FIG. 1 to FIG. 3 aswell as the flowchart of the gesture recognition method of FIG. 2. Instep S210 (corresponding to an analysis stage P1), the gesturerecognition device 100 obtains a hand image 310 through the imagecapturing device 120 and provides the hand image 310 to the processor110 to cause the processor 110 to analyze a gesture graphic 311 in thehand image 310. A pixel value in the region of the gesture graphic 311in the binarized hand image 310 is, for example, 255, and a pixel valueoutside the region of the gesture graphic 311 is, for example, 0, butthe disclosure is not limited thereto. In step S220 (corresponding to ananalysis stage P2), the processor 110 calculates an average of aplurality of coordinate values of the gesture graphic 311 to determine areference point 321 in the gesture graphic 311 of the hand image 310. Inother words, the processor 110 uses the graphic center point of thegesture graphic 311 as the reference point 321. In step S230(corresponding to analysis stages P3 to P5), the processor 110determines a farthest point 331 corresponding to the reference point 321in the gesture graphic 311, and the processor 110 determines a pluralityof radii having different lengths corresponding to a plurality ofcircular arc reference lines 351_1 to 351_10 based on a connecting line(having a length of r, for example) between the reference point 321 andthe farthest point 331. In the present embodiment, the plurality ofcircular arc reference lines 351_1 to 351_10 may respectively besemi-circular arc lines, and the plurality of circular arc referencelines are spaced apart at an equal interval. The radii of the pluralityof circular arc reference lines 351_1 to 351_10 may be as shown in Table1 below. However, the number and the interval of the circular arcreference lines of the disclosure are not limited to those shown inTable 1 below. In an embodiment, the number and the interval of thecircular arc reference lines may be correspondingly designed accordingto different gesture recognition requirements.

TABLE 1 Reference line Radius Circular arc reference line 351_1  r/10Circular arc reference line 351_2 2r/10 Circular arc reference line351_3 3r/10 Circular arc reference line 351_4 4r/10 Circular arcreference line 351_5 5r/10 Circular arc reference line 351_6 6r/10Circular arc reference line 351_7 7r/10 Circular arc reference line351_8 8r/10 Circular arc reference line 351_9 9r/10 Circular arcreference line 351_10 r

In step S240 (corresponding to an analysis stage P6), the processor 110determines an intersection point number of a plurality of intersectionpoints of each of the plurality of circular arc reference lines 351_1 to351_10 intersecting with the boundary of the gesture graphic 311 in acounterclockwise manner, for example. In the present embodiment, theboundary of the gesture graphic 311 refers to a borderline of a pixelvalue change, for example, from black (the pixel value of the regionoutside the gesture graphic is 0) to white (the pixel value of theregion in the gesture graphic is 255), or from white to black.Therefore, the intersection point number of the plurality ofintersection points of each of the plurality of circular arc referencelines 351_1 to 351_10 intersecting with the boundary of the gesturegraphic 311 may be as shown in Table 2 below. In the present embodiment,the processor 110 may select one of the plurality of circular arcreference lines 351_1 to 351_10 that has the highest intersection pointnumber with respect to the boundary of the gesture graphic 311 todetermine the number of fingers. Moreover, taking Table 2 as an example,the processor 110 may determine that the circular arc reference line351_6 has the most intersection points with the boundary of the gesturegraphic 311. For example, three intersection points 361, 363, and 365changing from black to white and three intersection points 362, 364, and366 changing from white to black are present between the circular arcreference line 351_6 and the boundary of the gesture graphic 311.Therefore, the processor 110 may determine that the number of fingers ofthe gesture graphic 311 is three based on the plurality of intersectionpoints 361 to 366 of the circular arc reference line 351_6. However, inother embodiments, if the plurality of circular arc reference lines351_1 to 351_10 include multiple circular arc reference lines equallyhaving the most intersection points, the processor 110 selects one thatis farthest from the reference point 321 as the basis for determiningthe number of fingers.

TABLE 2 Intersection point Intersection point number (from number (fromReference line black to white) white to black) Circular arc reference 00 line 351_1 Circular arc reference 0 0 line 351_2 Circular arcreference 0 0 line 351_3 Circular arc reference 1 1 line 351_4 Circulararc reference 2 2 line 351_5 Circular arc reference 3 3 line 351_6Circular arc reference 2 2 line 351_7 Circular arc reference 2 2 line351_8 Circular arc reference 2 2 line 351_9 Circular arc reference 1 0line 351_10

In step S250 (corresponding to an analysis stage P7), the processor 110selects the circular arc reference line 351_6, which has the highestintersection point number, as a first recognition boundary, and selectsthe circular arc reference line 351_9, which is the previous circulararc reference line to the circular arc reference line 351_10 farthestfrom the reference point, as a second recognition boundary. In thepresent embodiment, from all the intersection points of each of thecircular arc reference lines between the first recognition boundary andthe second recognition boundary, the processor 110 selects coordinatesof two intersection points that are adjacent to each other and arelocated in the gesture graphic, and calculates their center pointcoordinates to be defined as a finger skeleton point. Therefore, theplurality of circular arc reference lines 351_6 to 351_9 generate aplurality of finger skeleton points B1 to B7. In other words, theprocessor 110 is only required to analyze a portion of the hand image310. Next, according to a plurality of skeleton point connecting linesof the plurality of finger skeleton points B1 to B7, the processor 110determines whether the plurality of finger blocks of the gesture graphic311 conform to a trend in which at least two skeleton point connectinglines are approaching each other. The approaching trend means, forexample, that the shape of one finger block is approaching the shape ofanother finger block, but the disclosure is not limited thereto.However, the determination of the trend analysis (e.g., divergence orconvergence of multiple data over time) is a conventional technicalmeans commonly used in statistical analysis of various engineering orfinancial data. The trend analysis functions are also provided ingeneral spreadsheet software and conventionally publicly knowntechniques, which shall not be repeatedly described herein. In thepresent embodiment, the processor 110 respectively connects theplurality of finger skeleton points B1 to B7 in each of the fingerblocks to determine the plurality of skeleton point connecting lines.For example, the skeleton points B1 to B4 form a connecting line, andthe skeleton points B5 to B7 form another connecting line.

In step S260 (corresponding to the analysis stage P7), when theplurality of skeleton point connecting lines include at least twoskeleton point connecting lines that are approaching each other, theprocessor 110 determines that the plurality of finger blocks of thegesture graphic 311 conform to the approaching trend, and the processor110 performs step S270. Conversely, when none of the plurality ofskeleton point connecting lines are approaching each other, theprocessor 110 determines that the plurality of finger blocks of thegesture graphic 311 do not conform to the approaching trend, and theprocessor 110 performs step S210 again to obtain a next hand image.

In step S270 (corresponding to analysis stages P8 to P9), the processor110 selects the circular arc reference line 351_7, which is the nextcircular arc reference line to the circular arc reference line 351_6having the highest intersection point number, as a third recognitionboundary, and selects the circular arc reference line 351_10, which isfarthest from the reference point 321, as a fourth recognition boundary.In step S280, the processor 110 determines whether the plurality offinger blocks of the gesture graphic 311 between the third recognitionboundary and the fourth recognition boundary is connected into one. Inthis regard, as shown by a partial hand image 320 that is cut outbetween the third recognition boundary and the fourth recognitionboundary, since the plurality of finger blocks of the gesture graphic311 that are cut out between the third recognition boundary and thefourth recognition boundary are not connected into one (there are twoblocks in the partial hand image 320), the plurality of finger blocks ofthe gesture graphic 311 between the third recognition boundary and thefourth recognition boundary do not form a continuous graphic block.Therefore, the processor 110 determines that the gesture graphic 311 ofthe hand image 310 is not a pinch gesture (as, in general, the end ofthe thumb and the end of another finger in the pinch gesture are broughtinto contact with each other and connected together), and the processor110 performs step S210 again to obtain a next hand image. Accordingly,by analyzing a portion of the hand image 310 (it is only required toanalyze the image content between the two recognition boundaries), thegesture recognition device 100 of the present embodiment can accuratelyrecognize in real-time that the gesture graphic 311 of the hand image310 is not a pinch gesture, and it is not required to continuouslycompute or process the entire hand image 310.

FIG. 4 is a schematic view of analysis on another hand image accordingto an embodiment of the disclosure. Reference is made to FIG. 1, FIG. 2,and FIG. 4 as well as the flowchart of the gesture recognition method ofFIG. 2. In step S210 (corresponding to an analysis stage P1′), thegesture recognition device 100 obtains a hand image 410 through theimage capturing device 120 and provides the hand image 410 to theprocessor 110 to cause the processor 110 to analyze a gesture graphic411 in the hand image 410. A pixel value in the region of the gesturegraphic 411 in the hand image 410 is, for example, 255, and a pixelvalue outside the region of the gesture graphic 411 is, for example, 0,but the disclosure is not limited thereto. In step S220 (correspondingto an analysis stage P2′), the processor 110 calculates an average of aplurality of coordinate values of the gesture graphic 411 to determine areference point 421 in the gesture graphic 411 of the hand image 410. Inother words, the processor 110 uses the graphic center point of thegesture graphic 411 as the reference point 421. In step S230(corresponding to analysis stages P3′ to P5′), the processor 110determines a farthest point 431 corresponding to the reference point 421in the gesture graphic 311, and the processor 110 determines a pluralityof radii having different lengths corresponding to a plurality ofcircular arc reference lines 451_1 to 451_10 based on a connecting line(having a length of r, for example) between the reference point 421 andthe farthest point 431. In the present embodiment, the plurality ofcircular arc reference lines 451_1 to 451_10 may respectively besemi-circular arc lines, and the plurality of circular arc referencelines are spaced apart at an equal interval. The radii of the pluralityof circular arc reference lines 451_1 to 451_10 may be as shown in Table3 below. However, the number and the interval of the circular arcreference lines of the disclosure are not limited to those shown inTable 3 below. In an embodiment, the number and the interval of thecircular arc reference lines may be correspondingly designed accordingto different gesture recognition requirements.

TABLE 3 Reference line Radius Circular arc reference line 451_1  r/10Circular arc reference line 451_2 2r/10 Circular arc reference line451_3 3r/10 Circular arc reference line 451_4 4r/10 Circular arcreference line 451_5 5r/10 Circular arc reference line 451_6 6r/10Circular arc reference line 451_7 7r/10 Circular arc reference line451_8 8r/10 Circular arc reference line 451_9 9r/10 Circular arcreference line 451_10 r

In step S240 (corresponding to an analysis stage P6′), the processor 110determines an intersection point number of a plurality of intersectionpoints of each of the plurality of circular arc reference lines 451_1 to451_10 intersecting with the boundary of the gesture graphic 411 in acounterclockwise manner, for example. In the present embodiment, theboundary of the gesture graphic 411 refers to a borderline of a pixelvalue change, for example, from black (the pixel value of the regionoutside the gesture graphic is 0) to white (the pixel value of theregion in the gesture graphic is 255), or from white to black.Therefore, the intersection point number of the plurality ofintersection points of each of the plurality of circular arc referencelines 451_1 to 451_10 intersecting with the boundary of the gesturegraphic 411 may be as shown in Table 4 below. In the present embodiment,the processor 110 may select one of the plurality of circular arcreference lines 451_1 to 451_10 that has the highest intersection pointnumber with respect to the boundary of the gesture graphic 411 todetermine the number of fingers. Moreover, taking Table 4 as an example,the processor 110 may determine that the circular arc reference line451_7 has the most intersection points with the boundary of the gesturegraphic 411. For example, three intersection points 461, 463, and 465changing from black to white and three intersection points 462, 464, and466 changing from white to black are present between the circular arcreference line 451_7 and the boundary of the gesture graphic 411.Therefore, the processor 110 may determine that the number of fingers ofthe gesture graphic 411 is three based on the plurality of intersectionpoints 461 to 466 of the circular arc reference line 451_7. However, inother embodiments, if the plurality of circular arc reference lines451_1 to 451_10 include multiple circular arc reference lines equallyhaving the most intersection points, the processor 110 selects one thatis farthest from the reference point 421 as the basis for determiningthe number of fingers.

TABLE 4 Intersection point Intersection point number number Referenceline (black to white) (white to black) Circular arc reference 0 0 line451_1 Circular arc reference 0 0 line 451_2 Circular arc reference 0 0line 451_3 Circular arc reference 1 1 line 451_4 Circular arc reference1 1 line 451_5 Circular arc reference 1 2 line 451_6 Circular arcreference 3 3 line 451_7 Circular arc reference 2 2 line 451_8 Circulararc reference 1 1 line 451_9 Circular arc reference 1 0 line 451_10

In step S250 (corresponding to an analysis stage P7′), the processor 110selects the circular arc reference line 451_7, which has the highestintersection point number, as a first recognition boundary, and selectsthe circular arc reference line 451_9, which is the previous circulararc reference line to the circular arc reference line 451_10 farthestfrom the reference point, as a second recognition boundary. In thepresent embodiment, from all the intersection points of each of thecircular arc reference lines between the first recognition boundary andthe second recognition boundary, the processor 110 selects coordinatesof two intersection points that are adjacent to each other and arelocated in the gesture graphic, and calculates their center pointcoordinates to be defined as a finger skeleton point. Therefore, theplurality of circular arc reference lines 451_7 to 451_9 generate aplurality of finger skeleton points C1 to C6. In other words, theprocessor 110 is only required to analyze a portion of the hand image410. Next, according to a plurality of skeleton point connecting linesof the plurality of finger skeleton points C1 to C6, the processor 110determines whether the plurality of finger blocks of the gesture graphic411 conform to a trend in which at least two skeleton point connectinglines are approaching each other. In the present embodiment, theapproaching trend means, for example, that the shape of one finger blockis approaching the shape of another finger block, but the disclosure isnot limited thereto. In the present embodiment, the processor 110respectively connects the plurality of finger skeleton points C1 to C6in each of the finger blocks to determine the plurality of skeletonpoint connecting lines. For example, the skeleton point C1 is a singlepoint, the skeleton points C2 to C4 form a connecting line, and theskeleton points C5 to C6 form another connecting line.

In step S260 (corresponding to the analysis stage P7′), when theplurality of skeleton point connecting lines include at least twoskeleton point connecting lines that are approaching each other, theprocessor 110 determines that the plurality of finger blocks of thegesture graphic 411 conform to the approaching trend, and the processor110 performs step S270. Conversely, when none of the plurality ofskeleton point connecting lines are approaching each other, theprocessor 110 determines that the plurality of finger blocks of thegesture graphic 411 do not conform to the approaching trend, and theprocessor 110 performs step S210 again to obtain a next hand image.

In step S270 (corresponding to analysis stages P8′ to P9′), theprocessor 110 selects the circular arc reference line 451_8, which isthe next circular arc reference line to the circular arc reference line451_7 having the highest intersection point number, as a thirdrecognition boundary, and selects the circular arc reference line451_10, which is farthest from the reference point 421, as a fourthrecognition boundary. In step S280, the processor 110 determines whetherthe plurality of finger blocks of the gesture graphic 411 between thethird recognition boundary and the fourth recognition boundary isconnected into one. In this regard, as shown by a partial hand image 420that is cut out between the third recognition boundary and the fourthrecognition boundary, since the plurality of finger blocks of thegesture graphic 411 that are cut out between the third recognitionboundary and the fourth recognition boundary are connected into one, theplurality of finger blocks of the gesture graphic 411 between the thirdrecognition boundary and the fourth recognition boundary form acontinuous graphic block. Therefore, the processor 110 determines thatthe gesture graphic 411 of the hand image 410 is a pinch gesture. Theprocessor 110 performs step S290 to output a gesture recognition resultfor the backend application or the backend device to perform othercorresponding functions or operations. Accordingly, by analyzing aportion of the hand image 410 (it is only required to analyze the imagecontent between the two recognition boundaries), the gesture recognitiondevice 100 of the present embodiment can accurately recognize inreal-time that the gesture graphic 411 of the hand image 410 is a pinchgesture, and it is not required to continuously compute or process theentire hand image 410.

FIG. 5 is a flowchart of a gesture recognition method according to anembodiment of the disclosure. Referring to FIG. 1 and FIG. 5, thegesture recognition method of the present embodiment is applicable to atleast the gesture recognition device 100 of the embodiment of FIG. 1 tocause the gesture recognition device 100 to perform steps S510 to S560.In step S510, the gesture recognition device 100 obtains a hand imagethrough the image capturing device 120. In step S520, the gesturerecognition device 100 analyzes the hand image through the processor 110to determine a reference point in a gesture graphic of the hand image.In step S530, the processor 110 determines a plurality of circular arcreference lines by using the reference point as a center. In step S540,the processor 110 determines a plurality of intersection points of eachof the plurality of circular arc reference lines intersecting with aboundary of the gesture graphic. In step S550, the processor 110determines whether a plurality of finger blocks of the gesture graphicconform to an approaching trend according to the plurality of circulararc reference lines and the plurality of intersection points, so as tofurther determine whether the plurality of finger blocks of the gesturegraphic form a continuous graphic block. In step S560, when theplurality of finger blocks of the gesture graphic conform to theapproaching trend and form the continuous graphic block, the processor110 determines that the hand image is a hand pinch image. Therefore,according to the gesture recognition method of the present embodiment,the gesture recognition device 100 can accurately recognize the user'sgesture in real-time.

In addition, regarding the implementation details of the steps of thepresent embodiment and other implementation features of the gesturerecognition device 100, reference may be made to the contents of theforegoing embodiments of FIG. 1 to FIG. 4 to obtain sufficientteachings, suggestions, and implementation descriptions, which shall notbe repeatedly described herein.

In summary of the above, the gesture recognition method and the gesturerecognition device of the disclosure can analyze the hand image of theuser in real-time to first determine whether the plurality of fingerblocks of the gesture graphic in the partial hand image conform to theapproaching trend, and then determine whether the finger blocks in thepartial hand image form a continuous graphic block, so as to determinewhether the hand image of the user is a hand pinch image. Therefore, thegesture recognition method and the gesture recognition device of thedisclosure can realize the gesture recognition function withoutcontinuously computing the entire hand image data.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the disclosed embodimentswithout departing from the scope or spirit of the disclosure. In view ofthe foregoing, it is intended that the disclosure covers modificationsand variations provided that they fall within the scope of the followingclaims and their equivalents.

What is claimed is:
 1. A gesture recognition method comprising:obtaining a hand image, wherein the hand image comprises a gesturegraphic; determining a reference point in the gesture graphic;determining a plurality of circular arc reference lines by using thereference point as a center; determining a plurality of intersectionpoints of each of the circular arc reference lines intersecting with aboundary of the gesture graphic; determining whether at least two fingerblocks of a plurality of finger blocks of the gesture graphic conform toan approaching trend according to the circular arc reference lines andthe intersection points, and determining whether the at least two fingerblocks in a selected range of the gesture graphic form a continuousgraphic block; and when the at least two finger blocks of the gesturegraphic conform to the approaching trend and form the continuous graphicblock, determining that the hand image is a hand pinch image.
 2. Thegesture recognition method according to claim 1, wherein the step ofdetermining the reference point in the gesture graphic comprises:calculating an average of a plurality of coordinate values of thegesture graphic to obtain the reference point.
 3. The gesturerecognition method according to claim 1, wherein the step of determiningthe circular arc reference lines by using the reference point as thecenter comprises: determining a farthest point corresponding to thereference point in the gesture graphic; and determining a plurality ofradii having different lengths corresponding to the circular arcreference lines based on a connecting line between the reference pointand the farthest point.
 4. The gesture recognition method according toclaim 3, wherein the circular arc reference lines are respectivelysemi-circular arc lines, and the circular arc reference lines are spacedapart at an equal interval.
 5. The gesture recognition method accordingto claim 1, wherein the step of determining whether the at least twofinger blocks of the gesture graphic conform to the approaching trendcomprises: selecting one of the circular arc reference lines that has ahighest intersection point number as a first recognition boundary;selecting another one circular arc reference line, which is the previouscircular arc reference line to the circular arc reference line farthestfrom the reference point among the circular arc reference lines, as asecond recognition boundary; and determining whether the at least twofinger blocks of the gesture graphic between the first recognitionboundary and the second recognition boundary conform to the approachingtrend.
 6. The gesture recognition method according to claim 5, furthercomprising: from all the intersection points of each of the circular arcreference lines between the first recognition boundary and the secondrecognition boundary, selecting coordinates of two intersection pointsthat are adjacent to each other and located in the gesture graphic andcalculating their center point coordinates to be defined as a fingerskeleton point; and determining whether the at least two finger blocksof the gesture graphic conform to the approaching trend according to aplurality of skeleton point connecting lines of the finger skeletonpoints.
 7. The gesture recognition method according to claim 6, whereinthe step of determining whether the at least two finger blocks of thegesture graphic conform to the approaching trend according to theskeleton point connecting lines of the finger skeleton points comprises:respectively connecting the finger skeleton points in each of the fingerblocks to determine the skeleton point connecting lines.
 8. The gesturerecognition method according to claim 6, wherein the step of determiningwhether the at least two finger blocks of the gesture graphic conform tothe approaching trend according to the skeleton point connecting linesof the finger skeleton points comprises: when at least two of theskeleton point connecting lines are approaching each other, determiningthat the at least two finger blocks of the gesture graphic conform tothe approaching trend.
 9. The gesture recognition method according toclaim 1, wherein the step of determining whether the at least two fingerblocks in the selected range of the gesture graphic form the continuousgraphic block comprises: selecting one circular arc reference line,which is the next circular arc reference line to the circular arcreference line having a highest intersection point number among thecircular arc reference lines, as a third recognition boundary; selectinganother one of the circular arc reference lines that is farthest fromthe reference point as a fourth recognition boundary; and determiningwhether the at least two finger blocks of the gesture graphic betweenthe third recognition boundary and the fourth recognition boundary formthe continuous graphic block.
 10. The gesture recognition methodaccording to claim 1, wherein the hand image is a binarized image, and aregion in the gesture graphic and a region outside the gesture graphicof the hand image have different pixel values.
 11. A gesture recognitiondevice comprising: an image capturing device configured to obtain a handimage, wherein the hand image comprises a gesture graphic; and aprocessor, electrically coupled to the image capturing device,configured to analyze the gesture graphic of the hand image to determinea reference point in the gesture graphic, wherein the processordetermines a plurality of circular arc reference lines by using thereference point as a center, and determines a plurality of intersectionpoints of each of the circular arc reference lines intersecting with aboundary of the gesture graphic, wherein the processor determineswhether at least two finger blocks of a plurality of finger blocks ofthe gesture graphic conform to an approaching trend according to thecircular arc reference lines and the intersection points, and determineswhether the at least two finger blocks in a selected range of thegesture graphic form a continuous graphic block, wherein when the atleast two finger blocks of the gesture graphic conform to theapproaching trend and form the continuous graphic block, the processordetermines that the hand image is a hand pinch image.
 12. The gesturerecognition device according to claim 11, wherein the processorcalculates an average of a plurality of coordinate values of the gesturegraphic to obtain the reference point.
 13. The gesture recognitiondevice according to claim 11, wherein the processor determines afarthest point corresponding to the reference point in the gesturegraphic, and the processor determines a plurality of radii havingdifferent lengths corresponding to the circular arc reference linesbased on a connecting line between the reference point and the farthestpoint.
 14. The gesture recognition device according to claim 13, whereinthe circular arc reference lines are respectively semi-circular arclines, and the circular arc reference lines are spaced apart at an equalinterval.
 15. The gesture recognition device according to claim 11,wherein the processor selects one of the circular arc reference linesthat has a highest intersection point number as a first recognitionboundary, and the processor selects another one circular arc referenceline, which is the previous circular arc reference line to the circulararc reference line farthest from the reference point among the circulararc reference lines, as a second recognition boundary, wherein theprocessor determines whether the at least two finger blocks of thegesture graphic between the first recognition boundary and the secondrecognition boundary conform to the approaching trend.
 16. The gesturerecognition device according to claim 15, wherein, from all theintersection points of each of the circular arc reference lines betweenthe first recognition boundary and the second recognition boundary, theprocessor selects coordinates of two intersection points that areadjacent to each other and located in the gesture graphic and calculatestheir center point coordinates to be defined as a finger skeleton point,and the processor determines whether the at least two finger blocks ofthe gesture graphic conform to the approaching trend according to aplurality of skeleton point connecting lines of the finger skeletonpoints.
 17. The gesture recognition device according to claim 16,wherein the processor respectively connects the finger skeleton pointsin each of the finger blocks to determine the skeleton point connectinglines.
 18. The gesture recognition device according to claim 16, whereinwhen at least two of the skeleton point connecting lines are approachingeach other, the processor determines that the at least two finger blocksof the gesture graphic conform to the approaching trend.
 19. The gesturerecognition device according to claim 11, wherein the processor selectsone circular arc reference line, which is the next circular arcreference line to the circular arc reference line having a highestintersection point number among the circular arc reference lines, as athird recognition boundary, and the processor selects another one of thecircular arc reference lines that is farthest from the reference pointas a fourth recognition boundary, wherein the processor determineswhether the at least two finger blocks of the gesture graphics betweenthe third recognition boundary and the fourth recognition boundary formthe continuous graphic block.
 20. The gesture recognition deviceaccording to claim 11, wherein the hand image is a binarized image, anda region in the gesture graphic and a region outside the gesture graphicof the hand image have different pixel values.